# RECORD 670518142f78514470ad2ea85cc37f0ccb4483aa
# TITLE: Low-emission zones, modes of transport and house prices: evidence from Berlin’s commuter belt
# YEAR: 2022.0  VENUE: Transportation  DOI: 10.1007/s11116-022-10295-8
# AUTHORS: E. Aydin; Kathleen Kürschner Rauck
# PAGES: 49  CANDIDATE TABLE PAGES (1-based): [11, 19, 20, 37, 38, 39, 40, 41, 42]
# ABSTRACT: We study the impact of a tightening of a private driving restriction in Germany’s capital, the city of Berlin, on house prices in its affluent suburbs. Using geo-referenced data on train stations, motorway access points and offers of single-family houses for sale from Germany’s leading online property broker ImmobilienScout24 in a spatially staggered DiD framework, we find evidence for sizeable price growth premia for houses located in walking distance of train stations that lie within 30 min commuting duration to Berlin main station. Property located in immediate vicinity (5 min walking distance) of train stations within 30–40 min commuting duration, however, face penalties. Our findings are of relevance for the design of public infrastructure planning policies that seek to accommodate and facilitate changes in local demands for alternative and more environmentally sustainable modes of transport induced by private driving restrictions.


===== PAGE 1 (score 6, numeric-paren 0, table-words 0, var-words 6) =====

Vol.:(0123456789)
Transportation (2023) 50:1847–1895
https://doi.org/10.1007/s11116-022-10295-8
1 3
Low‑emission zones, modes of transport and house prices: 
evidence from Berlin’s commuter belt
Eren Aydin1 · Kathleen Kürschner Rauck2,3 
Published online: 15 June 2022 
© The Author(s) 2022
Abstract
We study the impact of a tightening of a private driving restriction in Germany’s capi-
tal, the city of Berlin, on house prices in its affluent suburbs. Using geo-referenced data 
on train stations, motorway access points and offers of single-family houses for sale from 
Germany’s leading online property broker ImmobilienScout24 in a spatially staggered DiD 
framework, we find evidence for sizeable price growth premia for houses located in walk-
ing distance of train stations that lie within 30 min commuting duration to Berlin main 
station. Property located in immediate vicinity (5 min walking distance) of train stations 
within 30–40 min commuting duration, however, face penalties. Our findings are of rel-
evance for the design of public infrastructure planning policies that seek to accommodate 
and facilitate changes in local demands for alternative and more environmentally sustain-
able modes of transport induced by private driving restrictions.
Keywords  Low-emission zone · House prices · Berlin (Germany)
 JEL Classification  R4 · R11 · R31 · Q52
Introduction
Internationally, environmental policy to reduce pollution levels caused by vehicle traffic 
is implemented most forcefully by means of private driving restrictions. This holds true 
also for member states of the European Union (EU). However, EU member states are free 
to pursue policies of their own choice to cope with pollution limits upheld by the EU. 
This freedom of choice makes evaluations of the policies chosen by EU member states 
highly relevant for decision-makers and also potentially informative for the design of future 
policies.
 *	 Kathleen Kürschner Rauck 
	
kathleen.kuerschner@unisg.ch
1	
Universität Hamburg (UHH), Hamburg, Germany
2	
Swiss Institute of Banking and Finance, University of St.Gallen (HSG), Unterer Graben 21, 
9000 St. Gallen, Switzerland
3	
Swiss Finance Institute (SFI), Geneva, Switzerland


===== PAGE 11 (score 20, numeric-paren 0, table-words 4, var-words 10) =====

1857
Transportation (2023) 50:1847–1895	
1 3
2017). The data cover, and identify, stations that serve regional traffic via trains and stations 
that serve local public transportation. We disregard information on bus and tram stations 
and manually checked the operation status of stations identified in the data as being closed. 
Our final data set covers only counties in Brandenburg that share a direct border with Ber-
lin, and identifies 227 train stations, which function as reference points from which we 
calculate the walking distance bands (described above) for individual property in our data 
with the STATA module osrmtime (Huber and Rust 2016) using the shortest walking dis-
tance routes between each pairwise combination of sampled properties and train stations.
For our spatial difference-in-differences analysis, we define treatment and control group 
based on these walking distances (i.e., a purely local attribute) of observed property to train 
stations. The policy studied, however, was implemented in Berlin. As our analysis focuses 
on potential effects in the commuter belt of Berlin, the LEZ in Berlin can be considered 
a non-local/distant policy treatment. In order to emphasize the importance of Berlin as a 
commuter destination to its surrounding regions we utilize special data on the total number 
of commuters to Berlin and other municipality-level characteristics, provided by the State 
Office for Construction and Transport (Landesamt für Bauen und Verkehr—LBV) as time 
series data refined from data by the State Office for Statistics Berlin-Brandenburg (Amt für 
Statistik Berlin-Brandenburg), and the Federal Employment Agency (Bundesagentur für 
Arbeit - BA). Panel (a) of Fig. 2 illustrates the relevance of Berlin for surrounding regions 
by displaying the share of the population in the respective municipalities in Brandenburg 
commuting into Berlin in 2008. Counties in Brandenburg, that are adjacent to Berlin have an 
average share of 10.2% of the population (or close to 40% of commuters) commuting to Ber-
lin. In contrast on average only 1.2% of the population (or roughly only 8.5% of commuters) 
from the other counties in Brandenburg commute to Berlin. A systematic pattern between 
commuter inflow into Berlin from its suburbs becomes evident: regions/municipalities 
located closer to Berlin show higher numbers of workers commuting to Berlin. This holds 
true for previous and later years, as well. We therefore, restrict Berlin’s commuter belt in our 
estimations to counties in Brandenburg sharing a direct border with Berlin. Nevertheless, 
Table 1   Summary statistics by 
pre- and post-LEZ period (full 
estimation sample)
The table shows the mean of each variable for the entire estimation 
sample (129,521 observations) by pre-LEZ (stage 3) period January 
2008–June 2009 (column (1)) and post-LEZ (stage 3) period Janu-
ary 2010–June 2011 (column (2)). Standard deviations are reported in 
square brackets
Pre-LEZ (stage 3)
Post-LEZ (stage 3)
(1)
(2)
House price [EUR]
198, 860
[117,977]
205, 442
[127,999]
log House price
12.067
[0.526]
12.081
[0.569]
Living space ­[m2]
134.830
[43.866]
136.829
[46.683]
Base area ­[m2]
871.641
[753.831]
914.932
[830.484]
# rooms
4.674
[1.267]
4.736
[1.314]
Age [years]
20.823
[31.286]
23.984
[33.448]
Under construction [%]
0.067
[0.250]
0.056
[0.230]
Detached house [%]
0.833
[0.373]
0.863
[0.344]
Observations
67,588
61,933


===== PAGE 12 (score 9, numeric-paren 0, table-words 1, var-words 7) =====

1858
	
Transportation (2023) 50:1847–1895
1 3
we also construct three commuting duration bands to analyze outcomes for different com-
muting distances, measured in driving duration, to Berlin main train station. The calculation 
of shortest driving durations is again done with the STATA module osrmtime (Huber and 
Rust 2016). Constructed commuting duration bands are divided into (i) 30 min or less, (ii) 
beyond 30–40 min, and (iii) beyond 40–60 min.13 Panel (b) of Fig. 2 displays the spatial dis-
tribution of train stations in Brandenburg and provides a visual reference for the constructed 
commuting bands. Out of the sampled 227 train stations, 33 are located in the closest com-
muting belt, 54 stations are located in 30–40 min driving duration from Berlin main station, 
59 train stations lie in the 40–60 min driving duration band, and the remaining 81 stations 
are located in 60 or more minutes driving duration to/from Berlin main station.
The third type of data we use contains information on the road network of Brandenburg, 
which we obtained from the Infrastructure for Spatial Information in the European Com-
munity (INSPIRE) and its corresponding web feature service (WFS) provided by the federal 
state of Brandenburg (Landesbetrieb Straßenwesen Brandenburg 2018). Metadata, such as 
geo-referenced motorway access points, are accessible via this interface. We used geographic 
Fig. 2   Population share of outbound commuters to Berlin (at municipality-level) and train stations in 
Brandenburg by commuting duration to Berlin main station. Notes Panel (a) displays the share of the popu-
lation in a respective municipality that is commuting to Berlin (darker shades of grey indicate higher shares 
of commuters). Panel (b) depicts exact (geo-referenced) locations of train stations for counties in Branden-
burg that share an administrative border with Berlin by commuting duration (marked by different symbols 
(see legend) and different shades of gray (darker shades indicate more distant locations)) to Berlin main 
station (marked by a cross). The LEZ inside the administrative borders of Berlin is also marked and high-
lighted by hatching
13  For our empirical analyses that explore stratified samples by commuting duration, we disregard distance 
bands in which train stations are located in more than a 60-minute drive to Berlin main station due to the 
small number of observations and their mismatch in terms of commuters to Berlin when compared to closer 
distance bands as illustrated in 2.


===== PAGE 19 (score 140, numeric-paren 111, table-words 2, var-words 3) =====

1865
Transportation (2023) 50:1847–1895	
1 3
Table 2   Treatment effects—baseline results (semi-annually)
Dependent variable log House Price
Treatment effects
(1)
(2)
(3)
(4)
(5)
(6)
Treatment regions
   DISTi,STN 5 min
0.0015
(0.0279)
0.0090
(0.0280)
0.0077
(0.0296)
0.0261
(0.0797)
0.0480
(0.0289)
−0.0735
(0.0578)
   DISTi,STN 5−10 min
−0.0064
(0.0162)
−0.0005
(0.0171)
−0.0060
(0.0168)
−0.0167
(0.0306)
−0.0036
(0.0233)
−0.0139
(0.0236)
   DISTi,STN 10−15 min
−0.0123
(0.0142)
−0.0071
(0.0143)
−0.0066
(0.0144)
0.0356
(0.0348)
−0.0069
(0.0208)
−0.0284
(0.0202)
   DISTi,STN 15−20 min
−0.0141
(0.0208)
−0.0106
(0.0217)
−0.0160
(0.0187)
−0.0055
(0.0493)
−0.0090
(0.0204)
−0.0269
(0.0232)
   DISTi,MOT 10 min
−0.0551
(0.0194)
∗∗∗
−0.0659
(0.0235)
∗∗∗
−0.0586
(0.0555)
−0.0561
(0.0392)
−0.0527
(0.0329)
Treatment effects—train station
   POSTQ110−Q210 × DISTi,STN 5 min
−0.0210
(0.0406)
−0.0239
(0.0410)
−0.0212
(0.0402)
0.0894
(0.1145)
−0.0797
(0.0330)
∗∗
0.0374
(0.0637)
   POSTQ310−Q410 × DISTi,STN 5 min
−0.0192
(0.0539)
−0.0213
(0.0541)
−0.0264
(0.0551)
0.0978
(0.1590)
−0.1312
(0.0546)
∗∗
0.0227
(0.0412)
   POSTQ111−Q211 × DISTi,STN 5 min
−0.0373
(0.0547)
−0.0394
(0.0554)
−0.0525
(0.0549)
0.0484
(0.1547)
−0.1268
(0.0438)
∗∗∗
−0.0072
(0.0711)
   POSTQ110−Q210 × DISTi,STN 5−10 min
0.0031
(0.0190)
0.0003
(0.0190)
−0.0002
(0.0190)
0.0101
(0.0398)
−0.0069
(0.0262)
−0.0091
(0.0337)
   POSTQ310−Q410 × DISTi,STN 5−10 min
0.0108
(0.0189)
0.0116
(0.0203)
0.0027
(0.0217)
−0.0455
(0.0456)
−0.0443
(0.0228)
∗
0.0424
(0.0389)
   POSTQ111−Q211 × DISTi,STN 5−10 min
0.0507
(0.0214)
∗∗
0.0498
(0.0224)
∗∗
0.0353
(0.0216)
0.0244
(0.0470)
−0.0342
(0.0282)
0.0915
(0.0387)
∗∗
   POSTQ110−Q210 × DISTi,STN 10−15 min
0.0060
(0.0187)
0.0030
(0.0181)
0.0035
(0.0167)
0.0071
(0.0464)
0.0082
(0.0229)
0.0149
(0.0262)
   POSTQ310−Q410 × DISTi,STN 10−15 min
0.0175
(0.0200)
0.0154
(0.0193)
0.0081
(0.0185)
−0.0039
(0.0461)
−0.0209
(0.0275)
0.0528
(0.0225)
∗∗
   POSTQ111−Q211 × DISTi,STN 10−15 min
−0.0061
(0.0201)
−0.0096
(0.0197)
−0.0172
(0.0193)
−0.0169
(0.0554)
−0.0549
(0.0300)
∗
0.0324
(0.0342)
   POSTQ110−Q210 × DISTi,STN 15−20 min
−0.0181
(0.0227)
−0.0180
(0.0234)
−0.0142
(0.0237)
−0.0019
(0.0575)
0.0123
(0.0289)
−0.0122
(0.0367)
   POSTQ310−Q410 × DISTi,STN 15−20 min
0.0069
(0.0232)
0.0055
(0.0230)
−0.0001
(0.0215)
0.0184
(0.0617)
0.0257
(0.0261)
−0.0082
(0.0282)
   POSTQ111−Q211 × DISTi,STN 15−20 min
0.0162
(0.0241)
0.0123
(0.0244)
0.0039
(0.0227)
−0.0093
(0.0478)
0.0043
(0.0218)
0.0320
(0.0360)
Treatment effects—motorway
   POSTQ110−Q210 × DISTi,MOT 10 min
0.0295
(0.0176)
∗
0.0437
(0.0213)
∗∗
0.0316
(0.0365)
0.0452
(0.0610)
0.0122
(0.0250)
   POSTQ310−Q410 × DISTi,MOT 10 min
0.0187
(0.0186)
0.0301
(0.0191)
0.0292
(0.0352)
0.0092
(0.0445)
0.0052
(0.0253)


===== PAGE 20 (score 23, numeric-paren 5, table-words 4, var-words 9) =====

1866
	
Transportation (2023) 50:1847–1895
1 3
The dependent variable is the log of the nominal house price posted. Neighborhood characteristics at 1 km grid level (from 2009) include the unemployment rate, the share 
of buildings that are predominantly in commercial use, and the share of the foreign-born population. Standard errors are clustered at the municipality level. ***, **, * denote 
statistical significance at the 1%, 5% and 10% level
Table 2   (continued)
Dependent variable log House Price
Treatment effects
(1)
(2)
(3)
(4)
(5)
(6)
   POSTQ111−Q211 × DISTi,MOT 10 min
0.0188
(0.0233)
0.0054
(0.0230)
0.0807
(0.0460)
∗
−0.0134
(0.0449)
−0.0512
(0.0130)
∗∗∗
   Property characteristics
Yes
Yes
Yes
Yes
Yes
Yes
   Neighborhood characteristics (1 km grid)
No
Yes
Yes
Yes
Yes
Yes
   Municipality fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
   Time fixed effects (quarters)
Yes
Yes
Yes
Yes
Yes
Yes
   Sample restrictions
None
None
Walking distance to train station:
≤ 40 min
≤ 40 min
≤ 40 min
≤ 40 min
&
commuting distance
train STN–Berlin main STN:
≤ 60-40 min
≤ 40-30 min
≤ 30 min
   # fixed effects (municipality level)
240
240
140
46
42
22
   Obs.
129,521
129,521
90,745
13,283
34,930
36,117
   Within R2
0.4541
0.4558
0.4738
0.4458
0.5127
0.5258


===== PAGE 21 (score 23, numeric-paren 0, table-words 6, var-words 11) =====

1867
Transportation (2023) 50:1847–1895	
1 3
of motorway access points were characterized by offer price growth premia compared to 
dwellings beyond 10 min driving distance to motorways. Anticipation of a reduction in 
negative externalities provided by (or associated with) such sites, and likewise adjacent 
roads, such as (noise) pollution, elevated traffic, and road congestion, may sign responsible 
for this finding. However, it should already be noted that coefficient estimates for proximity 
to motorways do not prove robust in the proceeding of this paper, which is why we refrain 
from putting much weight on the interpretation of the respective coefficients.
The specifications we considered so far employed the full estimation sample of detached 
and semi-detached houses listed for sale in the federal state of Brandenburg’s counties 
that share a border with Berlin in the periods January 2008–June 2009 (pre-LEZ (stage 3) 
period) and January 2010–June 2011 (post-LEZ (stage 3) period). We will consider next 
four regionally restricted sub-samples. The first sample restriction aims to obtain a more 
homogenous sub-sample of houses in the treatment and control regions by increasing their 
relative proximity. Specifically, we restrict the estimation sample to houses located within 
40 min walking distance to train stations, which eliminates from the control group property 
in very remote locations (-38,776 observations). The corresponding estimation results are 
shown in column (3) of Table 2. Associated price growth premia for houses located in 
5–10 min walking distance of train stations turn out no longer statistically significant in 
the first half of 2011 (the coefficient estimate is decreased in size, by about 1.5%-points, 
whereas the standard error is almost unchanged).
We next subject the sub-sample of house listings within 40 min walking distance of STNs 
to further regional restrictions so as to obtain more plausible long- and short-distance daily-
commuter belts around the city of Berlin. We use stratified estimation samples for this pur-
pose that are based on three commuting duration bands: For the long-distance daily-com-
muter belt, we consider only houses located within 40 min walking distance of train stations, 
from which the commuting duration (by car) to Berlin main station ranges between 60–40 
min (see column (4)), respectively, between 40–30 min in the next closest belt (see column 
(5)), and up to 30 min for the short-distance daily-commuter belt (see column (6)).22 House 
listings in the 60–40 min commuting duration band show no statistically significant price 
growth premia or penalties attached to train station proximity. Moreover, houses that are 
located within 40 min walking distance of stations and within 10 min driving distance to 
motorway access points receive statistically significant price growth premia (at the 10% level) 
of on average 8.1%-points only in the third half-year of the post-LEZ (stage 3) period. The 
latter finding, may again be attributable to (the anticipation of) lower congestion and (noise) 
pollution near motorways after the LEZ tightening on 1st January 2010. Likewise, nearby 
access to an alternative mode of transport (car) to accessible rail-road travel (in 40 min walk-
ing distance) may have been valued particularly strongly in regions at farther distance from 
Berlin, in which residents tend to rely more on a single mode of transport (car) for conven-
tional activities, such as shopping and recreation. Houses in the adjacent commuting dura-
tion band of 40–30 min driving duration that are listed for sale in immediate vicinity of train 
stations (in 5 min walking distance) exhibit sizeable price growth penalties (of on average 
7.97–13.12%-points) after the implementation of the third stage LEZ. Similarly, a tendency 
for smaller, yet still sizeable (and in the second half of 2010 also statistically significant) price 
growth penalties is observable for property in the 5–10 min walking distance range. This 
tendency is also observable for listings in the adjacent 10–15 min walking distance band, for 
22  Appendix Table 4 provides summary statistics for characteristics of house listings in each of these com-
muting duration bands (by distance to train stations) for the pre- and for the post-LEZ (stage 3) period.


===== PAGE 37 (score 25, numeric-paren 0, table-words 2, var-words 5) =====

1883
Transportation (2023) 50:1847–1895	
1 3
Table 3   Summary statistics by distance to train station, pre- and post-LEZ period (full estimation sample)
Columns (1) to (12) show the mean of each variable for property located within 5 min (columns (1) and (7)), beyond 5–10 min (columns (2) and (8)), beyond 10–15 min 
(columns (3) and (9)), beyond 15–20 min (columns (4) and (10)) and beyond 20–40 min (columns (5) and (11)) walking distance of train stations, respectively, for property 
located beyond the 40 min walking distance threshold (columns (6) and (12)). Averages are calculated for the pre-LEZ (stage 3) period January 2008-June 2009 (columns (1) 
to (6)) and the post-LEZ (stage 3) period January 2010–June 2011 (columns (7) to (12)). Standard deviations are reported in square brackets
Pre-LEZ
Post-LEZ
≤ 5 min
> 5–10 min
> 10–15 min > 15–20 min
> 20–40 min
> 40 min
≤ 5 min
> 5–10 min
> 10–15 min
> 15–20 min
> 20–40 min
 > 40 min
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
House price [EUR]
192, 872
[101,419]
182, 517
[103,361]
187, 596
[81,304]
195, 924
[98,635]
210, 866
[126,365]
195, 664
[135,248]
185, 732
[86,800]
198, 525
[121,562]
198, 850
[101,863]
206, 116
[127,857]
213, 350
[125,083]
203, 527
[143,502]
log house price
12.049
[0.516]
12.061
[0.463]
12.054
[0.434]
12.082
[0.461]
12.131
[0.504]
12.002
[0.622]
12.019
[0.508]
12.080
[0.478]
12.092
[0.482]
12.108
[0.515]
12.134
[0.534]
12.017
[0.676]
Living space [ m2]
134.701
[42.601]
133.028
[39.033]
132.370
[41.247]
133.852
[42.559]
134.505
[43.217]
137.452
[47.869]
145.314
[51.176]
133.685
[43.938]
137.445
[44.492]
137.225
[48.838]
136.280
[45.032]
137.507
[48.752]
Base area [ m2]
830.591
[627.239]
785.793
[573.406]
796.840
[644.182]
826.397
[639.402]
807.164
[633.304]
1, 030.935
[978.51]
989.217
[704.739]
822.375
[587.856]
850.682
[707.006]
870.161
[746.92]
863.439
[725.359]
1, 039.131
[1,064.899]
# rooms
4.608
[1.115]
4.619
[1.209]
4.611
[1.216]
4.575
[1.200]
4.674
[1.231]
4.774
[1.380]
5.022
[1.504]
4.584
[1.235]
4.778
[1.230]
4.731
[1.349]
4.686
[1.257]
4.805
[1.391]
Age [years]
24.053
[32.606]
20.011
[31.868]
18.257
[29.852]
18.634
[29.750]
18.352
[28.571]
25.623
[34.272]
39.014
[40.218]
24.739
[33.314]
22.873
[32.674]
21.387
[32.296]
21.645
[31.532]
26.633
[35.168]
Under construction [%]
0.074
[0.262]
0.093
[0.291]
0.065
[0.247]
0.071
[0.257]
0.071
[0.257]
0.052
[0.222]
0.033
[0.178]
0.058
[0.234]
0.061
[0.240]
0.058
[0.233]
0.062
[0.241]
0.048
[0.214]
Detached house [%]
0.841
[0.366]
0.879
[0.326]
0.840
[0.367]
0.868
[0.338]
0.825
[0.380]
0.804
[0.397]
0.956
[0.205]
0.899
[0.301]
0.853
[0.354]
0.888
[0.315]
0.858
[0.349]
0.842
[0.365]
Observations
1,612
7,772
9,011
8,736
20,744
19,713
1,254
6,649
7,703
7,958
19,306
19,063


===== PAGE 38 (score 33, numeric-paren 0, table-words 2, var-words 5) =====

1884
	
Transportation (2023) 50:1847–1895
1 3
Table 4   Summary statistics by distance to train station, pre- and post-LEZ period (stratified estimation samples by commuting duration)
Pre-LEZ
Post-LEZ
≤ 5 min
> 5–10 min
> 10–15 min
> 15–20 min
> 20–40 min
≤ 5 min
> 5–10 min
> 10–15 min
> 15–20 min
> 20–40 min
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
Commuting duration from train station to Berlin main station: ≤30 min
House price [EUR]
234, 127
[114,192]
229, 283
[107,136]
207, 569
[81,732]
216, 468
[110,260]
258, 908
[162,539]
224, 596
[87,717]
221, 599
[106,789]
225, 662
[120,987]
222, 497
[136,071]
249, 759
[142,872]
log house price
12.259
[0.454]
12.258
[0.399]
12.175
[0.370]
12.190
[0.422]
12.337
[0.474]
12.241
[0.412]
12.221
[0.413]
12.232
[0.414]
12.195
[0.463]
12.310
[0.466]
Living space [ m2]
154.175
[50.705]
139.200
[43.682]
130.966
[37.999]
135.288
[43.382]
140.970
[46.721]
154.815
[58.415]
135.280
[39.745]
139.996
[46.641]
137.917
[51.960]
139.077
[45.648]
Base area [ m2]
819.342
[484.478]
747.671
[598.671]
648.467
[298.375]
740.473
[377.803]
714.017
[434.424]
854.121
[617.857]
694.986
[313.665]
699.915
[352.042]
794.356
[752.613]
766.727
[571.673]
# rooms
4.761
[0.888]
4.809
[1.311]
4.591
[1.111]
4.608
[1.182]
4.814
[1.231]
5.044
[1.708]
4.647
[1.198]
4.835
[1.186]
4.683
[1.255]
4.754
[1.292]
Age [years]
30.581
[37.199]
21.214
[33.224]
14.856
[26.434]
15.156
[27.106]
16.850
[27.476]
27.618
[34.586]
24.498
[32.038]
19.152
[28.960]
16.381
[28.020]
19.026
[30.403]
Under construction [%]
0.110
[0.313]
0.087
[0.282]
0.088
[0.283]
0.081
[0.272]
0.081
[0.273]
0.056
[0.229]
0.052
[0.221]
0.058
[0.234]
0.065
[0.247]
0.071
[0.257]
Detached house [%]
0.931
[0.253]
0.848
[0.359]
0.780
[0.414]
0.877
[0.329]
0.776
[0.417]
0.980
[0.139]
0.864
[0.343]
0.834
[0.372]
0.878
[0.327]
0.811
[0.392]
Observations
465
2,719
3,878
4,211
7,687
306
2,446
3,223
3,801
7,381
Commuting duration from train station to Berlin main station: >30-40 min
House price [EUR]
191, 820
[91,768]
183, 144
[90,779]
180, 426
[80,933]
191, 182
[84,292]
190, 310
[87,883]
177, 632
[64,170]
197, 842
[135,129]
189, 195
[78,196]
213, 231
[88,101]
208, 632
[97,943]
log house price
12.092
[0.356]
12.044
[0.367]
12.022
[0.400]
12.080
[0.398]
12.067
[0.423]
12.026
[0.360]
12.089
[0.419]
12.071
[0.409]
12.192
[0.398]
12.152
[0.446]
Living space [ m2]
126.391
[34.637]
128.952
[31.350]
130.745
[41.201]
133.223
[41.116]
129.949
[39.729]
130.892
[39.293]
134.574
[47.729]
131.970
[37.999]
138.798
[44.334]
134.899
[43.644]
Base area [ m2]
777.867
[644.262]
762.577
[423.161]
825.346
[670.034]
865.588
[727.418]
782.437
[531.040]
885.215
[528.220]
810.611
[551.878]
850.877
[761.195]
852.498
[666.293]
826.979
[577.650]
# rooms
4.529
[1.140]
4.479
[1.030]
4.531
[1.197]
4.485
[1.108]
4.535
[1.226]
4.696
[1.246]
4.529
[1.164]
4.616
[1.119]
4.812
[1.353]
4.619
[1.222]
Age [years]
15.281
[24.470]
14.080
[26.583]
15.912
[28.507]
17.300
[28.075]
16.074
[26.619]
33.162
[36.980]
20.081
[30.609]
19.851
[30.872]
20.286
[30.263]
19.008
[28.647]


===== PAGE 39 (score 29, numeric-paren 0, table-words 3, var-words 5) =====

1885
Transportation (2023) 50:1847–1895	
1 3
Table 4   (continued)
Pre-LEZ
Post-LEZ
≤ 5 min
> 5–10 min
> 10–15 min
> 15–20 min
> 20–40 min
≤ 5 min
> 5–10 min
> 10–15 min
> 15–20 min
> 20–40 min
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
Under construction [%]
0.079
[0.270]
0.130
[0.336]
0.062
[0.241]
0.078
[0.268]
0.073
[0.260]
0.029
[0.168]
0.066
[0.249]
0.085
[0.279]
0.062
[0.242]
0.055
[0.227]
Detached house [%]
0.749
[0.434]
0.914
[0.280]
0.874
[0.332]
0.883
[0.322]
0.868
[0.338]
0.925
[0.264]
0.940
[0.237]
0.848
[0.359]
0.903
[0.296]
0.889
[0.314]
Observations
857
3,337
3,503
3,013
8,577
517
2,536
2,932
2,539
7,119
Commuting duration from train station to Berlin main station: >40-60 min
House price [EUR]
172, 304
[53,866]
156, 505
[103,828]
169, 003
[64,789]
157, 818
[63,918]
180, 516
[83,735]
193, 223
[103,924]
168, 234
[101,026]
182, 595
[74,739]
172, 315
[162,274]
182, 803
[123,307]
log house price
11.986
[0.423]
11.828
[0.500]
11.953
[0.440]
11.860
[0.529]
11.994
[0.515]
12.044
[0.537]
11.912
[0.474]
12.031
[0.422]
11.914
[0.540]
11.984
[0.501]
Living space [ m2]
134.929
[34.016]
128.516
[37.472]
142.324
[47.449]
131.642
[40.445]
133.878
[44.003]
156.669
[53.286]
128.358
[41.074]
148.034
[49.046]
134.738
[50.593]
137.549
[46.586]
Base area [ m2]
851.071
[420.426]
815.706
[558.355]
1, 096.511
[1,080.054]
943.631
[783.474]
880.061
[671.788]
1, 265.101
[990.815]
914.926
[818.143]
1, 123.312
[1,004.446]
1, 014.019
[691.435]
980.094
[840.182]
# rooms
4.782
[1.160]
4.496
[1.177]
4.906
[1.417]
4.738
[1.412]
4.699
[1.159]
5.390
[1.560]
4.633
[1.431]
5.129
[1.494]
4.803
[1.601]
4.717
[1.206]
Age [years]
21.155
[30.418]
26.767
[34.268]
28.553
[36.871]
27.712
[35.734]
19.438
[27.986]
49.003
[42.303]
25.614
[34.474]
29.099
[35.386]
27.413
[37.794]
24.421
[32.327]
Under construction [%]
0.000
[0.000]
0.028
[0.165]
0.028
[0.165]
0.047
[0.213]
0.055
[0.229]
0.014
[0.117]
0.070
[0.256]
0.019
[0.138]
0.038
[0.192]
0.038
[0.188]
Detached house [%]
0.973
[0.164]
0.873
[0.333]
0.930
[0.255]
0.813
[0.390]
0.818
[0.836]
0.983
[0.131]
0.889
[0.314]
0.895
[0.307]
0.903
[0.296]
0.865
[0.342]
Observations
110
1,385
1,073
907
3,167
287
1,182
1,027
1,147
2,998
Columns (1) to (10) show the mean of each variable for property located within 5 min (columns (1) and (6)), 5–10 min (columns (2) and (7)), 10–15 min (columns (3) and 
(8)), 15–20 min (columns (4) and (9)), and 20–40 min (columns (5) and (10)) walking distance of train stations. Averages are calculated for the pre-LEZ (stage 3) period Janu-
ary 2008-June 2009 (columns (1) to (5)) and the post-LEZ (stage 3) period January 2010–June 2011 (columns (6) to (10)). Standard deviations are reported in square brackets


===== PAGE 40 (score 140, numeric-paren 111, table-words 2, var-words 3) =====

1886
	
Transportation (2023) 50:1847–1895
1 3
Table 5   Treatment effects—baseline results with bootstrapped standard errors (semi-annually)
Dependent variable log House Price
Treatment effects
(1)
(2)
(3)
(4)
(5)
(6)
Treatment regions
   DISTi,STN 5 min
0.0015
(0.0283)
0.0090
(0.0285)
0.0077
(0.0307)
0.0261
(0.0884)
0.0480
(0.0306)
−0.0735
(0.0576)
   DISTi,STN 5−10 min
−0.0064
(0.0174)
−0.0005
(0.0185)
−0.0060
(0.0182)
−0.0167
(0.0371)
−0.0036
(0.0246)
−0.0139
(0.0227)
   DISTi,STN 10−15 min
−0.0123
(0.0147)
−0.0071
(0.0148)
−0.0066
(0.0140)
0.0356
(0.0353)
−0.0069
(0.0213)
−0.0284
(0.0209)
   DISTi,STN 15−20 min
−0.0141
(0.0207)
−0.0106
(0.0217)
−0.0160
(0.0192)
−0.0055
(0.0513)
−0.0090
(0.0207)
−0.0269
(0.0222)
   DISTi,MOT 10 min
−0.0551
(0.0199)
∗∗∗
−0.0659
(0.0232)
∗∗∗
−0.0586
(0.0620)
−0.0561
(0.0410)
−0.0527
(0.0404)
Treatment effects – train station
   POSTQ110−Q210 × DISTi,STN 5 min
−0.0210
(0.0418)
−0.0239
(0.0426)
−0.0212
(0.0414)
0.0894
(0.1305)
−0.0797
(0.0396)
∗∗
0.0374
(0.0643)
   POSTQ310−Q410 × DISTi,STN 5 min
−0.0192
(0.0551)
−0.0213
(0.0551)
−0.0264
(0.0566)
0.0978
(0.1822)
−0.1312
(0.0566)
∗∗
0.0227
(0.0461)
   POSTQ111−Q211 × DISTi,STN 5 min
−0.0373
(0.0543)
−0.0394
(0.0546)
−0.0525
(0.0581)
0.0484
(0.1841)
−0.1268
(0.0445)
∗∗∗
−0.0072
(0.0706)
   POSTQ110−Q210 × DISTi,STN 5−10 min
0.0031
(0.0202)
0.0003
(0.0203)
−0.0002
(0.0198)
0.0101
(0.0447)
−0.0069
(0.0273)
−0.0091
(0.0319)
   POSTQ310−Q410 × DISTi,STN 5−10 min
0.0108
(0.0213)
0.0116
(0.0231)
0.0027
(0.0219)
−0.0455
(0.0505)
−0.0443
(0.0244)
∗
0.0424
(0.0370)
   POSTQ111−Q211 × DISTi,STN 5−10 min
0.0507
(0.0229)
∗∗
0.0498
(0.0241)
∗∗
0.0353
(0.0230)
0.0244
(0.0529)
−0.0342
(0.0297)
0.0915
(0.0402)
∗∗
   POSTQ110−Q210 × DISTi,STN 10−15 min
0.0060
(0.0192)
0.0030
(0.0186)
0.0035
(0.0171)
0.0071
(0.0466)
0.0082
(0.0236)
0.0149
(0.0284)
   POSTQ310−Q410 × DISTi,STN 10−15 min
0.0175
(0.0204)
0.0154
(0.0198)
0.0081
(0.0187)
−0.0039
(0.0486)
−0.0209
(0.0278)
0.0528
(0.0242)
∗∗
   POSTQ111−Q211 × DISTi,STN 10−15 min
−0.0061
(0.0200)
−0.0096
(0.0199)
−0.0172
(0.0186)
−0.0169
(0.0583)
−0.0549
(0.0310)
∗
0.0324
(0.0360)
   POSTQ110−Q210 × DISTi,STN 15−20 min
−0.0181
(0.0227)
−0.0180
(0.0232)
−0.0142
(0.0244)
−0.0019
(0.0609)
0.0123
(0.0303)
−0.0122
(0.0343)
   POSTQ310−Q410 × DISTi,STN 15−20 min
0.0069
(0.0244)
0.0055
(0.0241)
−0.0001
(0.0213)
0.0184
(0.0639)
0.0257
(0.0278)
−0.0082
(0.0283)
   POSTQ111−Q211 × DISTi,STN 15−20 min
0.0162
(0.0248)
0.0123
(0.0253)
0.0039
(0.0222)
−0.0093
(0.0517)
0.0043
(0.0228)
0.0320
(0.0353)
Treatment effects – motorway
   POSTQ110−Q210 × DISTi,MOT 10 min
0.0295
(0.0197)
0.0437
(0.0219)
∗∗
0.0316
(0.0415)
0.0452
(0.0703)
0.0122
(0.0284)
   POSTQ310−Q410 × DISTi,MOT 10 min
0.0187
(0.0199)
0.0301
(0.0212)
0.0292
(0.0393)
0.0092
(0.0487)
0.0052
(0.0364)


===== PAGE 41 (score 23, numeric-paren 5, table-words 4, var-words 9) =====

1887
Transportation (2023) 50:1847–1895	
1 3
Table 5   (continued)
Dependent variable log House Price
Treatment effects
(1)
(2)
(3)
(4)
(5)
(6)
   POSTQ111−Q211 × DISTi,MOT 10 min
0.0188
(0.0256)
0.0054
(0.0248)
0.0807
(0.0525)
−0.0134
(0.0460)
−0.0512
(0.0423)
   Property characteristics
Yes
Yes
Yes
Yes
Yes
Yes
   Neighborhood characteristics (1 km grid)
No
Yes
Yes
Yes
Yes
Yes
   Municipality fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
   Time fixed effects (quarters)
Yes
Yes
Yes
Yes
Yes
Yes
   Sample restrictions
None
None
Walking distance to train station
≤ 40 min
≤ 40 min
≤ 40 min
≤ 40 min
&
commuting duration
train STN–Berlin main STN:
≤ 60-40 min
≤ 40-30 min
≤ 30 min
   # fixed effects (municipality level)
240
240
140
46
42
22
   Obs.
129,521
129,521
90,745
13,283
34,930
36,117
   Within R2
0.4541
0.4558
0.4738
0.4458
0.5127
0.5258
The dependent variable is the log of the nominal house price posted. Neighborhood characteristics at 1 km grid level (from 2009) include the unemployment rate, the share 
of buildings that are predominantly in commercial use, and the share of the foreign-born population. Standard errors are bootstrapped with 500 replications. ***, **, * denote 
statistical significance at the 1%, 5% and 10% level


===== PAGE 42 (score 152, numeric-paren 122, table-words 2, var-words 2) =====

1888
	
Transportation (2023) 50:1847–1895
1 3
Table 6   Evolution of treatment effects—stratified estimation samples by commuting duration with boot-
strapped standard errors (semi-annually)
Dependent variable log House Price
Treatment effects
(1)
(2)
(3)
(4)
Treatment regions
   DISTi,STN 5 min
−0.0844
(0.0583)
−0.1693
(0.1056)
0.0474
(0.0286)
∗
0.0495
(0.0594)
   DISTi,STN 5−10 min
−0.0280
(0.0253)
−0.1354
(0.0416)
∗∗∗
−0.0070
(0.0249)
−0.0742
(0.0416)
∗
   DISTi,STN 10−15 min
−0.0385
(0.0212)
∗
−0.0708
(0.0375)
∗
−0.0090
(0.0208)
−0.1258
(0.0403)
∗∗∗
   DISTi,STN 15−20 min
−0.0297
(0.0222)
−0.0928
(0.0500)
∗
−0.0101
(0.0211)
−0.0044
(0.0394)
Treatment effects – train station
   POSTQ110−Q210 × DISTi,STN 5 min
0.0431
(0.0646)
0.1031
(0.0906)
−0.0790
(0.0385)
∗∗
−0.0805
(0.0482)
∗
   POSTQ310−Q410 × DISTi,STN 5 min
0.0330
(0.0450)
0.1258
(0.1019)
−0.1258
(0.0546)
∗∗
−0.1284
(0.0804)
   POSTQ111−Q211 × DISTi,STN 5 min
−0.0077
(0.0704)
0.1199
(0.1550)
−0.1292
(0.0442)
∗∗∗
−0.1307
(0.0975)
   POSTQ311−Q411 × DISTi,STN 5 min
0.0319
(0.0670)
0.1934
(0.1624)
−0.1295
(0.0452)
∗∗∗
−0.1319
(0.1137)
   POSTQ112−Q212 × DISTi,STN 5 min
0.0505
(0.0753)
0.2437
(0.1819)
−0.1481
(0.0599)
∗∗
−0.1498
(0.1333)
   POSTQ312−Q412 × DISTi,STN 5 min
−0.0510
(0.0792)
0.1767
(0.2254)
−0.1612
(0.1081)
−0.1633
(0.1477)
   POSTQ110−Q210 × DISTi,STN 5−10 min
−0.0063
(0.0313)
0.0693
(0.0361)
∗
−0.0067
(0.0276)
0.0400
(0.0438)
   POSTQ310−Q410 × DISTi,STN 5−10 min
0.0453
(0.0372)
0.1627
(0.0444)
∗∗∗
−0.0418
(0.0244)
∗
0.0311
(0.0525)
   POSTQ111−Q211 × DISTi,STN 5−10 min
0.0916
(0.0393)
∗∗
0.2524
(0.0709)
∗∗∗
−0.0326
(0.0305)
0.0690
(0.0597)
   POSTQ311−Q411 × DISTi,STN 5−10 min
0.0807
(0.0425)
∗
0.2850
(0.0765)
∗∗∗
−0.0557
(0.0399)
0.0710
(0.0655)
   POSTQ112−Q212 × DISTi,STN 5−10 min
0.0020
(0.0686)
0.2484
(0.1074)
∗∗
0.0319
(0.0422)
0.1875
(0.1006)
∗
   POSTQ312−Q412 × DISTi,STN 5−10 min
−0.0209
(0.0540)
0.2672
(0.1046)
∗∗
0.1051
(0.0488)
∗∗
0.2885
(0.0999)
∗∗∗
   POSTQ110−Q210 × DISTi,STN 10−15 min
0.0155
(0.0280)
0.0398
(0.0233)
∗
0.0065
(0.0238)
0.0882
(0.0290)
∗∗∗
   POSTQ310−Q410 × DISTi,STN 10−15 min
0.0550
(0.0236)
∗∗
0.0901
(0.0373)
∗∗
−0.0236
(0.0284)
0.1049
(0.0386)
∗∗∗
   POSTQ111−Q211 × DISTi,STN 10−15 min
0.0316
(0.0357)
0.0801
(0.0498)
−0.0577
(0.0306)
∗
0.1172
(0.0522)
∗∗
   POSTQ311−Q411 × DISTi,STN 10−15 min
0.0057
(0.0468)
0.0654
(0.0619)
−0.0058
(0.0326)
0.2162
(0.0528)
∗∗∗
   POSTQ112−Q212 × DISTi,STN 10−15 min
0.0044
(0.0594)
0.0770
(0.0780)
−0.0329
(0.0435)
0.2352
(0.0765)
∗∗∗
   POSTQ312−Q412 × DISTi,STN 10−15 min
0.0240
(0.0485)
0.1088
(0.0822)
−0.0224
(0.0401)
0.2921
(0.0893)
∗∗∗
   POSTQ110−Q210 × DISTi,STN 15−20 min
−0.0104
(0.0341)
0.0351
(0.0380)
0.0155
(0.0303)
0.0110
(0.0437)
   POSTQ310−Q410 × DISTi,STN 15−20 min
−0.0089
(0.0278)
0.0601
(0.0402)
0.0274
(0.0278)
0.0211
(0.0501)
   POSTQ111−Q211 × DISTi,STN 15−20 min
0.0295
(0.0346)
0.1243
(0.0463)
∗∗∗
0.0031
(0.0227)
−0.0046
(0.0583)
   POSTQ311−Q411 × DISTi,STN 15−20 min
0.0544
(0.0331)
∗
0.1730
(0.0655)
∗∗∗
−0.0145
(0.0335)
−0.0246
(0.0731)
   POSTQ112−Q212 × DISTi,STN 15−20 min
0.0204
(0.0400)
0.1650
(0.0789)
∗∗
−0.0109
(0.0315)
−0.0223
(0.0871)
   POSTQ312−Q412 × DISTi,STN 15−20 min
0.0340
(0.0438)
0.2031
(0.0734)
∗∗∗
0.0213
(0.0281)
0.0080
(0.0950)
   linear trend
0.0118
(0.0075)
0.0262
(0.0091)
∗∗∗
   linear trend × DISTi,STN 5 min
−0.0167
(0.0142)
−0.0001
(0.0095)
   linear trend × DISTi,STN 5−10 min
−0.0214
(0.0072)
∗∗∗
−0.0136
(0.0076)
∗
   linear trend × DISTi,STN 10−15 min
−0.0062
(0.0070)
−0.0233
(0.0061)
∗∗∗
   linear trend × DISTi,STN 15−20 min
−0.0125
(0.0076)
0.0009
(0.0066)


===== PAGE 43 (score 16, numeric-paren 0, table-words 4, var-words 8) =====

1889
Transportation (2023) 50:1847–1895	
1 3
Table 6   (continued)
Dependent variable log House Price
Treatment effects
(1)
(2)
(3)
(4)
Sample restrictions
walking distance to train station: ≤ 40 min
&
commuting duration train STN–Berlin main STN:
≤ 30 min
> 30-40 min
   # fixed effects (municipality level)
22
42
   Obs.
48,450
47,949
   Within R2
0.5337
0.5336
0.5355
0.5359
The dependent variable is the log of the nominal house price posted. Specifications (1) through (4) include 
municipality and time fixed effects as well as property- and neighborhood-specific characteristics at 1 km 
grid level (from 2009), which include the unemployment rate, the share of buildings that are predominantly 
in commercial use, and the share of the foreign-born population. Standard errors are bootstrapped with 500 
replications. ***, **, * denote statistical significance at the 1%, 5% and 10% level